In a system for encoding a sound such as speech or audio, a linear predictive coding (LPC) coefficient is used to represent a short-term frequency characteristic of the sound. The LPC coefficient is obtained in a form of dividing an input sound in frame units and minimizing energy of a prediction error for each frame. However, the LPC coefficient has a large dynamic range, and a characteristic of a used LPC filter is very sensitive to a quantization error of the LPC coefficient, and thus stability of the filter is not guaranteed.
Therefore, an LPC coefficient is quantized by converting the LPC coefficient into another coefficient in which stability of the filter is easily confirmed, interpolation is advantageous, and a quantization characteristic is good. It is mostly preferred that an LPC coefficient is quantized by converting the LPC coefficient into a line spectral frequency (LSF) or an immittance spectral frequency (ISF). Particularly, a scheme of quantizing an LSF coefficient may use a high inter-frame correlation of the LSF coefficient in a frequency domain and a time domain, thereby increasing a quantization gain.
An LSF coefficient exhibits a frequency characteristic of a short-term sound, and in a case of frame in which a frequency characteristic of an input sound sharply varies, an LSF coefficient of a corresponding frame also sharply varies. However, a quantizer including an inter-frame predictor using a high inter-frame correlation of an LSF coefficient cannot perform proper prediction for a sharply varying frame, and thus, quantization performance decreases. Therefore, it is necessary to select an optimized quantizer in correspondence with a signal characteristic of each frame of an input sound.